Within the field of computing, many scenarios involve automated language translation between input provided in a source language and output provided in a target language. Such techniques may not only include automated translation from a source natural language to a target natural language, but also between a first modality and a second modality of the same language (e.g., spoken and written words), and between two domains within the same language (e.g., describing a topic in technical language and in non-technical language).
Many types of language translation techniques may be applied to such scenarios. For example, for a request to translate a word sequence in a source language into a target language, a device may utilize a phrase table to map various phrases in the source language to equivalent phrases in the target language (e.g., using an English-to-French word reference identifying corresponding pairs or sets of words in each language). Additionally, the device may apply a language model that is capable of identifying, among two or more candidate selections and orderings of words in the target language, the candidate that is likely to be the most accurate and/or fluent translation of the word sequence in the source language. Such architectures may utilize a wide variety of techniques to perform the phrase selection and/or language modeling in order to provide automated translation techniques presenting an acceptable accuracy and/or fluency.